Apache Solr was always ready to be extended. What was only needed is a binary with the code and the modification of the Solr configuration file, the solrconfig.xml and we were ready. It was even simpler with the Solr APIs that allowed us to create various configuration elements – for example, request handlers. What’s more, the default Solr distribution came with a few plugins already – for example, the Data Import Handler or Learning to Rank.
As Elasticsearch users are pushing the limits of how much data they can store on an Elasticsearch node, they sometimes run out of heap memory before running out of disk space. This is a frustrating problem for these users, as fitting as much data per node as possible is often important to reduce costs. But why does Elasticsearch need heap memory to store data? Why doesn't it only need disk space?
This post was written by InfluxAce Nikki Attea A long time ago in a galaxy far, far away the phrase “May the Force be with you” originated to wish those good luck before parting ways, oftentimes before a journey or battle.
There’s no question that subscription-based businesses are an incredibly popular revenue model in today’s economy. While single transaction revenue models tend to fluctuate due to the seasonality of markets, subscription plans offer much more consistent and predictable revenues. Although the subscription revenue model can certainly be advantageous over one-off transactions, these businesses are also notoriously challenging to keep subscribers active on their plan.
As we connect with customers we increasingly hear the need for teams to be more predictive with their data. A big challenge is uncertainty around how to get started, especially when much of their data is unstructured. At Splunk, our goal is to make data — and machine learning — accessible for a broad range of users. The good news is, with machine learning doing even more work on your behalf, you don’t need to be a data scientist to use these advanced capabilities.
Microsoft Power BI is a business analytics solution providing interactive visualizations and business intelligence capabilities from data and provides an interface that is simple enough for admins to create their own reports and dashboards. Data inputs to Power BI can come from multiple sources – Excel worksheets, CSV files, database tables, log files, the web, etc. It then employs smart visualizations and built-in AI technologies on that data to turn it into interactive insights.
Let’s be honest. No one wakes up in the morning thinking of reasons to contact customer support. It’s tedious, onerous, and can eat into your evening Netflix time. Thankfully, most brands realize that customer experiences drive brand loyalty and repeat purchases.
Even though most of us have spent this month working from home or furloughed due to COVID-19, glitches certainly haven’t been taking a break. We’re still relying on intricate software systems to keep the world moving, and we have little ability to maintain them in person. What’s more, changing usage patterns have stressed global networks in ways that are hard to anticipate. As a result, we find ourselves in a perfect storm for technical outages.
LogDNA is adding the ability to store and view raw lines, allowing customers to debug with logs in their unaltered form. If you’ve ever looked at your logs and noticed that the timestamp was different than what you expected, it is usually due to a long latency between the event and processing time of the logs. Depending on the size of the latency, we may update the log timestamp to order them accurately and to provide a cleaner and more intuitive search experience.
